Role-Based Decision Mining for Multiagent Emergency Response Management

Emergency response operations require availability of tools that would allow fast and clear description of situation, generation of effective solutions for situation management, selection of a right decision maker and supplying him/her necessary data. During decision making support a large amount of raw data describing current situation, users preferences, found solutions and final decisions done by decision maker are accumulated in the repository. To make these data useful, methods of data mining can be applied. The goal of decision mining is to find "rules" explaining under which circumstances one activity is to be selected rather than the other one. The paper presents results of a research concerning mining of decisions stored in user profiles to find common preferences for different roles of decision makers participating in emergency response operations. These preferences could be used as a basis for building of decision trees allowing (semi)automatically selection of best decisions in a typical situation. Modeling of an emergency response management system implementing the research results has been done using software agents playing roles of different types of the system users. Case studies related to fire and accident response operations have been used.

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